Evaluation of a scientific data search infrastructure
The ability to search over large scientific datasets has become crucial to next-generation scientific discoveries as data generated from scientific facilities grow dramatically. In previous work, we developed and deployed ScienceSearch, a search infrastructure for scientific data which uses machine learning to automate metadata creation. Our current deployment is deployed atop a container based platform at a HPC center. In this article, we present an evaluation and discuss our experiences with the ScienceSearch infrastructure. Specifically, we present a performance evaluation of ScienceSearch's infrastructure focusing on scalability trends. The obtained results show that ScienceSearch is able to serve up to 130 queries/min with latency under 3 s. We discuss our infrastructure setup and evaluation results to provide our experiences and a perspective on opportunities and challenges of our search infrastructure.